Biometric-oriented personal identification techniques are becoming increasingly important in protecting personal property, such as laptop computers and cellular phones, preventing credit card and calling card fraud, limiting access to security areas, computers and information, and ensuring security for electronic commerce. Biometric identification techniques employ physical traits, measurements and other characteristics specific to an individual. These characteristics include, but are not limited to, voice prints, hand prints, fingerprints, retina patterns, and signature analysis. Typically, biometric identification and verification techniques compare an individual's stored biometric data against newly obtained biometric data when the individual desires use of a protected item, or access to a protected area or information. Due to its inherent nature, biometric data has the advantage of always being available for user identification and verification. However, also by its inherent nature, due to the vagaries of the human body, biometric data is often difficult to acquire in a consistent manner to yield an unambiguous measure of identity.
The fingerprint biometric is probably the most widely used and researched biometric identification technique. Existing technology allows the relevant features of a fingerprint to be represented in a few hundred bytes of data. Furthermore, the computer hardware required for recording and comparing fingerprint data can be centralized and accessed through a telecommunications network thereby allowing costs to be amortized across many transactions.
The disadvantage of biometric identification and verification, and in particular fingerprint identification, is in acquiring an accurate image of the fingerprint each time an individual desires to use or access the protected item. The problems associated with acquiring an accurate fingerprint image include sensor device dependent variables, such as hardware defects and deterioration, and individual conditions, such as the moisture content and temperature of the feature being imaged.
Accordingly, there is needed a sensor device employing methodology that accounts for sensor device variability, human biometric variability and adjusts for variable conditions that are present when imaging an individual's biometric features.